Research And Application Of Complex Network Model

According to recent years' researches, we found that many real systems can be described with a complex network. These complex networks have some common characteristics, such as small average path length, big clustering coefficient, power-law degree distribution, etc, these characteristics are the gradual evolvements' results for the complex networks to finish some special functions. The systems that can be described with complex networks include both artificial systems and natural systems. Thereby, complex networks gradually became an important way to study complex systems, and the models of complex networks are important tools to study the complex networks.This paper analyzed in detail and realized three complex network models: small world grid model, social acquaintance network model, scale-free network model. In the small world grid model, we presented and realized a new way to select long link according to the probability, this method adds up the probability based on the distance between the source node and the current node, simplified the selection of the long link and achieved the expectant effect. For complex social acquaintance model, we presented and realized a simple social model, it keeps most characteristics and behaviors of the old model, but it is easy to realize. We realized scale-free network model. At last, we gave a contrastive analysis of the three models according to the results of the experiments.